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Agile Pilot Lab

An experimental laboratory for AI innovation. Where ideas become intelligent solutions.

  • Experimental AI development
  • Full-stack AI solutions
  • Open-source innovation

What We Experiment With

AI Research & Prototyping

We explore emerging AI technologies, building experimental prototypes that push the boundaries of what's possible with intelligent automation.

  • LangChain framework experimentation
  • Multi-agent system architectures
  • Novel AI workflow patterns
Full-Stack Development

We develop experimental AI solutions for our own innovation purposes, not custom client applications. Our focus is on moving towards 100% agentic AI systems that operate without human intervention or support, pushing the boundaries of autonomous AI capabilities.

  • Aim for 100% agentic AI development
  • Autonomous systems with zero human intervention
  • Self-operating AI applications
AI Research & Prototyping

We explore emerging AI technologies, building experimental prototypes that push the boundaries of what's possible with intelligent automation.

  • LangChain framework experimentation
  • Multi-agent system architectures
  • Novel AI workflow patterns
Full-Stack Development

We develop experimental AI solutions for our own innovation purposes, not custom client applications. Our focus is on working towards 100% agentic AI systems that operate without human intervention or support, pushing the boundaries of autonomous AI capabilities.

  • Aim for 100% agentic AI development
  • Autonomous systems with zero human intervention
  • Self-operating AI applications

Why Our Lab

Experimental Innovation

Deep research into AI technologies, exploring cutting-edge approaches to intelligent automation.

Open Source First

Transparent development with public repositories and collaborative innovation.

Rapid Prototyping

Quick experimentation cycles to test ideas and validate concepts before full implementation.

Full-Stack Approach

Complete AI solutions from research to deployment on modern cloud infrastructure.

Our Laboratory Focus

We experiment with emerging AI technologies, building open-source solutions that advance the field of artificial intelligence.

Current research areas:

  • LangChain framework optimization
  • Multi-agent coordination systems
  • Cloud-native AI deployment patterns

Featured Project

AI-Generated Service Booking Platform

Aim for 100% AI-coded field technician scheduling system

An ambitious experiment to build a commercially viable service call booking system for field technicians using largely AI-generated code. Beyond development, the platform will be enhanced with AI agents for market analysis, Google search optimization, Google Ads management, and social media automation—demonstrating the full potential of AI in business operations.

Aim for 100% AI Generated
Fully AI-coded application
Field Service System
Technician booking & scheduling
AI Marketing Agents
SEO, Ads & social media automation
AI Development Stack
Django
HTML/CSS
Bootstrap 5
PostgreSQL
JavaScript
GitHub Copilot

AI Marketing Agents
SEO Optimization
Google Ads Management
Social Media Automation

Aim for 100% AI-generated codebase

Featured Research

AI-Powered Multi-Document RAG System

100% AI-coded document analysis and question-answering platform

An advanced Retrieval-Augmented Generation (RAG) system that processes multiple PDF and Excel files simultaneously, enabling cross-document analysis and intelligent question-answering. The system combines document processing, vector embeddings, and conversational AI to create a comprehensive knowledge base from your document collection.

Actual 100% AI Generated
Fully AI-coded application
Multi-Document Processing
PDF & Excel file analysis with cross-referencing
Smart Search & Retrieval
Vector-based semantic search across all documents
AI Development Stack
LangChain
RAG framework & document processing
OpenAI GPT-4o-mini
Language model for Q&A
FAISS
Vector database for semantic search
PyPDF & Pandas
PDF & Excel processing

RAG Components
Document Loaders → Text Splitters → Embeddings → Vector Store → Retrieval Chain → Q&A

Complete RAG pipeline with multi-file support